Non-autoregressive Decoding (NAR)   
Consider TSP as a link prediction task: each edge may belong/not belong to the optimal TSP solution independent of one another [1]}.
We define the edge predictor as a two layer MLP on the node embeddings produced by the final GNN encoder layer \(L\) , following Joshi et al. [2]}.
For adjacent nodes \(i\)  and \(j\) , we compute the unnormalized edge logits:
\(\hat{p}_{ij} = W_2 \Big ( \text{ReLU} \; \big ( W_1 \big ( \left[ \; h_{G}, \; h_{i}^{L}, \; h_{j}^{L} \; \right] \big ) \big ) \Big ), \;\ \text{where} \;\ h_{G} = \frac{1}{n} \sum _{i=0}^{n} h_i^{L},\) 
